Abstract

Water pollution caused by harmful heavy metal ions (HMIs) can significantly impact aquatic ecosystems and pose a high risk to human health. In this work, equipped with ultra-high fluorescence brightness, efficient energy transfer, and environmentally friendly performance, polymer dots (Pdots) were employed to construct a pattern recognition fluorescent HMIs detection platform. A single-channel unary Pdots differential sensing array was first developed to identify multiple HMIs with 100% classification accuracy. Then an "all-in-one" multiple Förster resonance energy transfer (FRET) Pdots differential sensing platform was constructed to discriminate HMIs in the artificial polluted water samples and actual water samples, exhibiting high classification accuracy in distinguishing HMIs. The proposed strategy leverages the compounded cumulative differential variation of diverse sensing channels for analytes, which is anticipated to find extensive applications in other fields for detection purposes.

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